CN117039922A - Wind turbine generator active frequency support control method based on sliding mode algorithm - Google Patents
Wind turbine generator active frequency support control method based on sliding mode algorithm Download PDFInfo
- Publication number
- CN117039922A CN117039922A CN202310675564.4A CN202310675564A CN117039922A CN 117039922 A CN117039922 A CN 117039922A CN 202310675564 A CN202310675564 A CN 202310675564A CN 117039922 A CN117039922 A CN 117039922A
- Authority
- CN
- China
- Prior art keywords
- sliding mode
- power
- frequency
- wind turbine
- active
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 31
- 230000004044 response Effects 0.000 claims abstract description 99
- 238000012546 transfer Methods 0.000 claims description 82
- 239000011159 matrix material Substances 0.000 claims description 67
- 230000001360 synchronised effect Effects 0.000 claims description 36
- 238000013016 damping Methods 0.000 claims description 30
- 230000008093 supporting effect Effects 0.000 claims description 16
- 230000008859 change Effects 0.000 claims description 13
- 238000013461 design Methods 0.000 claims description 12
- 239000012141 concentrate Substances 0.000 claims description 6
- 230000009897 systematic effect Effects 0.000 claims description 6
- 238000013459 approach Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 230000001419 dependent effect Effects 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 2
- 238000010248 power generation Methods 0.000 claims description 2
- 238000011084 recovery Methods 0.000 abstract description 2
- 230000035945 sensitivity Effects 0.000 abstract 1
- 238000011217 control strategy Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000005251 gamma ray Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 3
- 238000009499 grossing Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000010485 coping Effects 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
- H02J3/241—The oscillation concerning frequency
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Control Of Eletrric Generators (AREA)
Abstract
The invention relates to a sliding mode algorithm-based active frequency support control method for a wind turbine, belongs to the technical field of wind turbine control, and aims to solve the problem that the traditional PD or PID controller is high in sensitivity to time disturbance and is used for controlling frequencies to cause non-ideal dynamic performance; firstly, establishing a system frequency state equation containing wind power active frequency support based on wind turbine generator load shedding control and a frequency response model; then, combining the strong disturbance rejection capability and robustness of a sliding mode algorithm, and fully considering the frequency adjustment performance of the wind turbine generator, and designing a sliding mode disturbance observer and a sliding mode frequency controller; and finally, determining parameter value ranges of a sliding mode disturbance observer and a sliding mode frequency controller based on the Lyapunov method, and ensuring the overall stable operation of the proposed control method. The active frequency support control method can rapidly utilize the reserved power reserve of the wind turbine, improve the active frequency support capacity of the wind turbine, and improve the system frequency deviation and the system frequency recovery speed.
Description
Technical Field
The invention belongs to the technical field of wind turbine generator control, and particularly relates to a wind turbine generator active frequency support control method based on a sliding mode algorithm.
Background
The system frequency is inevitably affected by various uncertainty disturbance to generate fluctuation, and for a low-inertia power system containing high-proportion wind power, as the wind power is connected with a grid through a power electronic device and has no active frequency supporting capability, when impact load disturbance is generated in the system, the frequency supporting effect is difficult to meet the system requirement. Therefore, the active frequency supporting capability of the fan is provided, and the fan is a necessary requirement for ensuring the safe and stable operation of a low-inertia power system.
At present, the main flow of active frequency support control methods of wind turbines can be divided into short-term frequency support control and long-term frequency support control according to the frequency support length. Short-term frequency support control, such as virtual inertia, droop, compensates for system inertia by releasing kinetic energy stored on the fan rotor to simulate the inertial response of a conventional synchronous machine; and (3) long-term frequency support control, namely performing load shedding operation on the wind turbine set by obtaining pitch angle control through overspeed control to reserve a certain mechanical power reserve, performing frequency support through the reserved mechanical power reserve when frequency drop occurs, and adjusting frequency deviation to zero.
But most of the above methods are based on frequency adjustment by PD or PID controllers. From a practical point of view, the power system under high proportion wind power access is a time-varying nonlinear system that is affected by various disturbances, including external disturbances, parameter uncertainties, and unmodeled dynamics. Whereas conventional PD or PID controllers are highly sensitive to time-varying disturbances, their use in frequency control can lead to non-ideal dynamic performance.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a control method for supporting the active frequency of a wind turbine based on a sliding mode algorithm, so as to improve the supporting capacity of the active frequency of the wind turbine, realize the expected system frequency performance and enhance the stability of the system frequency.
The technical scheme adopted by the invention is as follows:
a wind turbine generator active frequency support control method based on a sliding mode algorithm comprises the following steps:
step 1: combining a traditional frequency response model and a wind turbine generator load shedding output power linearization model to construct a system frequency response model containing wind turbine generator participation in frequency modulation;
step 2: decomposing and deforming the active frequency support transfer function of the wind turbine in the system frequency response model, setting the synchronous unit frequency response power, load fluctuation and wind energy fluctuation in the model as concentrated disturbance power, and establishing a system frequency state equation under the active frequency support of the wind turbine;
Step 3: a sliding mode disturbance observer for estimating the concentrated disturbance power is designed based on a super-distortion sliding mode algorithm by taking the system frequency deviation and an additional power control signal as input signals;
step 4: the method comprises the steps of taking zero system frequency deviation and concentrated disturbance power as control targets, constructing a sliding mode surface capable of converting a system frequency state equation into a linear equation, and adopting a linear system control design method to design a sliding mode surface matrix according to expected system frequency performance;
step 5: based on a super-twist sliding mode algorithm, designing a sliding mode control rate of a driving system on a sliding mode surface, and constructing a sliding mode frequency controller to enable the frequency modulation power tracking of the wind turbine to concentrate disturbance power;
step 6: and a Lyapunov method is adopted to construct a Lyapunov function to determine the parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller, so that the proposed control method can be operated globally and stably.
Preferably, the wind turbine generator load shedding output power linearization model in step 1 has an active frequency support control interface for utilizing wind turbine generator mechanical power reserve to input an additional power control signal Δp output for the slip mode frequency controller f The dynamic change of the output power of the wind turbine generator under the active frequency support control can be reflected.
The system frequency response model with the wind turbine generator participating in frequency modulation comprises a traditional frequency response model and a wind turbine generator load shedding output power linearization model, wherein wind speed fluctuation, load fluctuation and additional power control signals are input, and the output is system frequency deviation, so that the system frequency dynamic change under the condition that the wind turbine generator and the synchronous unit participate in frequency modulation together can be reflected when uncertain load disturbance or wind speed disturbance occurs.
Preferably, the concentrated disturbance power ΔP described in step 2 d The synchronous machine frequency response power is contained, so that the synchronous machine information is not needed when the wind turbine generator output power is tracked and concentrated to disturb the power, and the frequency modulation tasks of the synchronous machine and the wind turbine generator can be coordinated. For example, when a disturbance (load disturbance or wind speed disturbance) occurs, the synchronous machine set participates in frequency adjustment, the concentrated disturbance power is correspondingly reduced, and the wind turbine set tracking target becomes reduced concentrated disturbance power without bearing the whole frequency modulation task. Therefore, the wind turbine generator can participate in frequency support in cooperation with the synchronous turbine generator, and provide active frequency support for the system.
The active frequency of the wind turbine generator supports a transfer function, and an additional power control signal delta P which can be output by a sliding mode frequency controller f Reflecting the change condition of the active frequency support power of the wind turbine, describing the frequency regulation performance of the wind turbine, and can be expressed as:
wherein: h w 、D w Respectively an inertia constant and a damping coefficient of the wind turbine generator. Omega rdel0 The rotor speed of the wind turbine is the rotor speed when the wind turbine is at a stable working point.For variation of rotor speed delta omega r The associated mechanical power response transfer function.For the change quantity delta omega of the speed of the rotor under the load-shedding operation of the wind turbine generator r The associated active power response transfer function.Is a rotor speed response transfer function related to the unbalanced power Δp. A is that w 、B w And the constants of the transfer functions are respectively supported by the active frequencies of the wind turbine generator.
The decomposition and deformation of the active frequency support transfer function of the wind turbine generator set are used for forming active frequency support power delta P w,f Intermediate variable Δp of (1) w,m Thereby converting the 2-dimensional system frequency state equation into 3-dimensional. The active frequency support transfer function of the wind turbine generator can be divided into a control signal delta P with additional power f The related active frequency supports the power intermediate variable response transfer function, and the intermediate variable deltap w,m The associated active frequency-dependent power response transfer functions are expressed as:
wherein: h w 、D w Respectively an inertia constant and a damping coefficient of the wind turbine generator. Omega rdel0 The rotor speed of the wind turbine is the rotor speed when the wind turbine is at a stable working point.For variation of rotor speed delta omega r The associated mechanical power response transfer function.For the change quantity delta omega of the speed of the rotor under the load-shedding operation of the wind turbine generator r The associated active power response transfer function. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively.
The system frequency state equation can reflect the dynamic change of the system frequency, is the basis for constructing a sliding mode disturbance observer and a sliding mode frequency controller, and can be expressed as follows:
wherein:as a system parameter matrix, Δx= [ ΔfΔp ] w,f ΔP w,m ] T As a system state variable matrix, u=Δp f Is a control item. ΔP f An additional power control signal is output for the sliding mode frequency controller. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. Δf is the system frequency deviation, ΔP w,f For active frequency support power provided by wind turbines ΔP w,m Is delta P w,f Is an intermediate variable of (a). ΔP d ＝ΔP L -ΔP s -ΔP w,v To concentrate the disturbance power ΔP L For load fluctuation, ΔP s For synchronizing the frequency supporting dynamics of the unit, delta P w,v Is the fluctuation of wind energy caused by the fluctuation of wind speed. d, d w 、d s The access proportion of the wind turbine generator and the access proportion of the synchronous machine are respectively. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively.
Preferably, the sliding mode disturbance observer in step 3 does not need other complicated information, and only needs to use the external system frequency deviation Δf and the additional power control signal Δp output by the internal sliding mode frequency controller f Accurate estimation of the concentrated disturbance power can be achieved, which reduces implementation difficulty for practical systems, and can be expressed as:
；
wherein: h s 、D s The inertia constant and the damping coefficient of the power system are respectively. d, d w And (5) the ratio of the wind turbine generator set is accessed.The system frequency bias estimated for the sliding mode disturbance observer. />The concentrated disturbance power estimated for the sliding mode disturbance observer. ΔP f An additional power control signal is output for the sliding mode frequency controller. />And supporting a transfer function for the active frequency of the wind turbine. g 1 、g 2 The sliding mode control items designed by the super-distortion sliding mode algorithm ensure the accuracy of the estimation result, and can be expressed as follows:
Wherein: h s 、D s The inertia constant and the damping coefficient of the power system are respectively. ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively.Represented as systematic frequency offset estimation error. sign is a sign function.
Preferably, the system frequency state equation described in step 4, which is re-represented by the system state variable matrix redesigned according to the control target, can be expressed as:
wherein:b is a system parameter matrix s ＝[0 1] T To control the matrix, Δx s ＝[Δf Δη] T For a system state variable matrix redesigned according to control objectives, u=Δp f Is a control item. ΔP f An additional power control signal is output for the sliding mode frequency controller. d, d w And (5) the ratio of the wind turbine generator set is accessed. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. A is that w 、B w Intermediate variable response transfer function and active frequency support power respectivelyConstant of the rate response transfer function. Δf, Δη, Δζ are expressed as:
wherein: Δf is the system frequency deviation. ΔP w,f Power is supported for the active frequency provided by the wind turbine. ΔP w,m Is delta P w,f Is an intermediate variable of (a). d, d w And (5) the ratio of the wind turbine generator set is accessed.The concentrated disturbance power estimated for the sliding mode disturbance observer. B (B) w The constant of the power response transfer function is supported for the active frequency.
The sliding mode surface can be expressed as:
s w ＝Δζ-[K 1 K 2 ]Δx s ＝Δζ-KΔx s ＝0；
wherein: s is(s) w Is a sliding mode variable. K is a sliding mode surface matrix. Δx s ＝[ΔfΔη] T For a system state variable matrix redesigned according to the control objective, Δζ is a system state variable, which can be expressed as:
wherein: Δf is the system frequency deviation. ΔP w,f Power is supported for the active frequency provided by the wind turbine. ΔP w,m Is delta P w,f Is an intermediate variable of (a). d, d w And (5) the ratio of the wind turbine generator set is accessed.The concentrated disturbance power estimated for the sliding mode disturbance observer. B (B) w The constant of the power response transfer function is supported for the active frequency.
The linear equation is obtained by converting a system frequency state equation when the sliding mode frequency controller driving system is positioned on a sliding mode surface, and can be expressed as follows:
；
wherein: a is that s B is a system parameter matrix s For the control matrix, K is a sliding mode surface matrix, deltax s Is a system state variable matrix redesigned according to the control objective. A is that cl For a linear system matrix, the matrix A can be configured by designing a sliding mode surface matrix K through a linear system control design method cl To obtain the desired system frequency dynamics.
The linear system control design method comprises a linear quadratic adjustment method and a characteristic allocation method, wherein the linear quadratic adjustment method is selected to obtain the expected dynamic performance of the system frequency.
Preferably, the sliding mode frequency controller in step 5 outputs the additional power control signal ΔP f And controlling the wind turbine to output mechanical power reserve reserved in advance and actively supporting the system frequency. Output of additional power control signal ΔP f By slip-form control ratio u=u e +u s ＝ΔP f Decision, can be expressed as
Wherein: k is a sliding mode surface matrix. s is(s) w Is a sliding mode variable.Is a system parameter matrix, b s ＝[0 1] T Is a control matrix, deltax s ＝[ΔfΔη] T Is a state variable. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. d, d w And (5) the ratio of the wind turbine generator set is accessed. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively. v represents the sliding mode approach rate based on the super-warping algorithm, and can be expressed as:
wherein: s is(s) w Is a sliding mode variable. Gamma ray 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller. sign is a sign function.
Preferably, the parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller in the step 6 can be represented by the following inequality constraint:
wherein: d (D) 1 、D 2 The boundaries of the concentrated disturbance power differential and the system frequency disturbance term, respectively. ψ= [ - ρ 1 2] T ，λ min {U w Is a semi-positive definite matrix U w Is used to determine the minimum characteristic value of the (c), λ min {N w Is a semi-positive definite matrix N w Is the minimum characteristic value of U w 、N w Can be expressed as:
wherein: ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively. Gamma ray 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller.
The beneficial effects are that: the active frequency support control method of the wind turbine generator can adjust the sliding mode surface matrix through the linear system control design method, so that the system frequency deviation and the tracking error of the wind turbine generator to the concentrated disturbance power are converged to zero according to the expected speed when the system is positioned on the sliding mode surface, the expected system frequency performance is realized, the system frequency deviation and the system frequency recovery speed are improved, and the stability of the system frequency is enhanced.
Drawings
FIG. 1 is a schematic overall flow chart of the present invention.
FIG. 2 is a diagram of a frequency response model of a system with wind turbines participating in frequency modulation.
FIG. 3 is a simplified system frequency response model diagram of a wind turbine active frequency support of the present invention.
FIG. 4 is a control block diagram of a sliding mode disturbance observer according to the invention.
Fig. 5 is a system damping diagram for each parameter of the sliding surface matrix K of the present invention.
FIG. 6 is an uncertainty disturbance map of the present invention.
FIG. 7 is a graph of the result of concentrated disturbance power estimation under an uncertainty load disturbance of the present invention, wherein FIG. 7 (a) is a graph of the result of concentrated disturbance power estimation; fig. 7 (b) is an estimation error map; fig. 7 (c) is a total estimation error map.
FIG. 8 is a graph of the active frequency support results under an uncertainty load disturbance of the present application, where FIG. 8 (a) is a graph of system frequency bias; FIG. 8 (b) is a graph of total system frequency bias; FIG. 8 (c) is a fan output power bias diagram; fig. 8 (d) is a dc side capacitance diagram.
FIG. 9 is a graph of the result of concentrated disturbance power estimation at uncertain wind speed disturbance according to the present application, wherein FIG. 9 (a) is a graph of the result of concentrated disturbance power estimation; fig. 9 (b) is an estimation error map; fig. 9 (c) is a total estimation error map.
FIG. 10 is a graph of active frequency support results under uncertain wind speed disturbances according to the present application, wherein FIG. 10 (a) is a graph of systematic frequency bias; FIG. 10 (b) is a graph of total system frequency bias; fig. 10 (c) is a fan output power deviation map, and fig. 10 (d) is a dc side capacitance deviation map with fan output power.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
The invention is described in further detail below with reference to the accompanying drawings 1-10 of the specification:
as shown in fig. 1, a wind turbine generator active frequency support control method based on a sliding mode algorithm includes the following steps:
step 1: combining a traditional frequency response model and a wind turbine generator load shedding output power linearization model to construct a system frequency response model containing wind turbine generator participation in frequency modulation;
a system frequency response model containing the wind turbine participating in frequency modulation is shown in fig. 2, and comprises a traditional frequency response model and a wind turbine load shedding output power linearization model. The input is wind speed fluctuation, load fluctuation and additional power control signals, and the output is system frequency deviation, so that the dynamic change of the system frequency under frequency modulation can be reflected when the wind turbine generator and the synchronous machine set jointly participate in the occurrence of uncertain load disturbance or wind speed disturbance.
The traditional frequency response model part is used for reflecting the system frequency change under unbalanced power, and comprises synchronous unit response and system inertia response which are respectively expressed as:
wherein: Δf, ΔP u Respectively, system frequency deviation and system unbalanced power. N is the number of synchronous units, F Hi The proportion of the output power of the high-pressure boiler of the turbine part of the ith synchronous unit, K mi Mechanical power gain factor R for ith synchronous machine set i Is the difference adjustment coefficient T of the ith synchronous machine set gi The time constant of the speed regulator part of the ith synchronous machine set. k is an automatic power generation control parameter. d, d s The access proportion of the synchronous machine set is obtained. H s 、D s Respectively a system inertia constant and a system damping.
The wind turbine generator load shedding output power linearization model is used for reflecting the change of the wind turbine generator output power under the control of active frequency support, and comprises a wind energy capturing part, a rotor speed response part and an active power response part which are respectively expressed as:
wherein: ΔP m 、Δω r 、ΔP e 、ΔP del 、ΔP f The mechanical power variable quantity, the rotor speed variable quantity, the active power variable quantity, the load shedding active power variable quantity and the additional power control signal of the wind turbine generator respectively,representation and Δω r Related wind energy capture transfer function, +.>Representation and DeltaV w Related wind energy capture transfer function, +.>Representing a rotor speed response transfer function related to the unbalanced power ΔP>Representation and Δω r Related load shedding activeA power response transfer function; expressed as:
wherein: v (V) w0 And omega rdel0 And (5) a stable working point under the load shedding operation of the wind turbine generator. ρ and R are the air density and blade length, respectively. k (k) 0 、k 1 And k 2 Is a constant coefficient. p is the pole pair number, k g Is the gear box ratio. H w 、D w Respectively an inertia constant and a damping coefficient of the wind turbine generator. k (k) del 、k opt 、C del The load shedding coefficient, the optimal coefficient and the load shedding wind energy utilization coefficient are respectively adopted.
And (3) to (9) of the comprehensive formula, the active frequency support transfer function of the wind turbine and the wind energy fluctuation transfer function of the wind turbine can be obtained, and the wind energy fluctuation transfer functions are respectively expressed as follows:
wherein: h w 、D w Respectively an inertia constant and a damping coefficient of the wind turbine generator. Omega rdel0 The rotor speed of the wind turbine is the rotor speed when the wind turbine is at a stable working point.Representation and Δω r Related wind energy capture transfer function, +.>Representation and DeltaV w Related wind energy capture transfer function, +.>Representing the rotor speed response transfer function in relation to the unbalance power ap,representation and Δω r An associated load shedding active power response transfer function. A is that w 、B w And supporting a constant of a transfer function for the active frequency of the wind turbine. C (C) w Is a constant of a wind energy fluctuation transfer function of the wind turbine generator.
Step 2: decomposing and deforming the active frequency support transfer function of the wind turbine generator in the system frequency response model, setting the synchronous unit frequency response power, load fluctuation and wind energy fluctuation in the model as concentrated disturbance power, and establishing a system frequency state equation under the active frequency support of the wind turbine generator.
The simplified system frequency response model under the support of the active frequency of the wind turbine is shown in FIG. 3, and the transfer function of the active frequency support of the wind turbine can be divided into the control signal delta P of the additional power f The related active frequency supports the power intermediate variable response transfer function, and the intermediate variable deltap w,m The associated active frequency-dependent power response transfer functions are expressed as:
wherein: h w 、D w Respectively an inertia constant and a damping coefficient of the wind turbine generator. Omega rdel0 The rotor speed of the wind turbine is the rotor speed when the wind turbine is at a stable working point.For variation of rotor speed delta omega r The associated mechanical power response transfer function.For the change quantity delta omega of the speed of the rotor under the load-shedding operation of the wind turbine generator r The associated active power response transfer function. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively.
Based on the simplified system frequency response model shown in fig. 3, the system frequency state equation under the support of the active frequency of the wind turbine can be expressed as follows:
wherein:as a system parameter matrix, Δx= [ ΔfΔp ] w,f ΔP w,m ] T As a system state variable matrix, u=Δp f Is a control item. ΔP f An additional power control signal is output for the sliding mode frequency controller. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. Δf is the system frequency deviation, ΔP w,f For active frequency support power provided by wind turbines ΔP w,m Is delta P w,f Is an intermediate variable of (a). ΔP d ＝ΔP L -ΔP s -ΔP w,v To concentrate the disturbance power ΔP L For load fluctuation, ΔP s For synchronizing the frequency supporting dynamics of the unit, delta P w,v Is the fluctuation of wind energy caused by the fluctuation of wind speed. d, d w 、d s The access proportion of the wind turbine generator and the access proportion of the synchronous machine are respectively. A is that w 、B w Constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function, respectively。
Step 3: and a sliding mode disturbance observer for estimating the concentrated disturbance power is designed based on a super-distortion sliding mode algorithm by taking the system frequency deviation and an additional power control signal as input signals.
The control block diagram of the sliding mode disturbance observer is shown in fig. 4, and the input is the control signal delta P output by the sliding mode frequency controller f And the system frequency deviation delta f is convenient and simple to acquire. Output as concentrated disturbance power estimation valueThe specific formula can be expressed as:
wherein: h s 、D s The inertia constant and the damping coefficient of the power system are respectively. d, d w And (5) the ratio of the wind turbine generator set is accessed. The system frequency bias estimated for the sliding mode disturbance observer. />The concentrated disturbance power estimated for the sliding mode disturbance observer. ΔP f An additional power control signal is output for the sliding mode frequency controller. />And supporting a transfer function for the active frequency of the wind turbine. g 1 、g 2 The sliding mode control items designed by the super-distortion sliding mode algorithm ensure the accuracy of the estimation result, and can be expressed as follows:
wherein: h s 、D s The inertia constant and the damping coefficient of the power system are respectively. ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively.Represented as systematic frequency offset estimation error. sign is a sign function. To weaken buffeting of the sliding mode variable motion trail when reaching a stable point, the symbol function sign () of the sliding mode observer control item is smoothed, which can be expressed as:
wherein: sigma is a very small normal number. When the sliding mode variable is far away from the sliding mode surface, the normal number hardly influences the output result of the sign function. When the sliding mode variable is close to the sliding mode surface, the normal number can reduce the output of the sign function, so that buffeting of the sliding mode variable motion trail is weakened.
Combining equation (14) with equation (15), the estimated error dynamics of the sliding mode disturbance observer can be described as a standard form of the following super-twisted sliding mode algorithm:
Wherein: h s 、D s The inertia constant and the damping coefficient of the power system are respectively. ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively.Represented as systematic frequency offset estimation error. />Representing the estimated error of the concentrated disturbance power. sign is a sign function. For concentrated disturbance power ΔP d ＝ΔP L -ΔP s -ΔP w,v For instance, due to load disturbance ΔP L Frequency modulation dynamic delta P of synchronous generator s Wind energy fluctuation Δp caused by wind speed fluctuation w,v Is always bounded. Reasonable assumption 1 can thus be made: differential +.>Is always bounded, has a positive constant, satisfies
Step 4: and constructing a sliding mode surface capable of converting a system frequency state equation into a linear equation by taking zero system frequency deviation and concentrated disturbance power of the wind turbine generator set as control targets, and designing a sliding mode surface matrix according to expected system frequency performance by adopting a linear system control design method.
To ensure stability of the system frequency, the various powers in the power system should be kept balanced. When the load is disturbed by delta P L Or wind energy disturbance ΔP caused by wind speed fluctuation w,v When this happens, the control objective of the sliding mode frequency controller is to adjust ΔP f Forcing system state variable tracking Δf=0 and Thus, the new state variable may be defined as:
wherein: Δf is the system frequency deviation. ΔP w,f Power is supported for the active frequency provided by the wind turbine. ΔP w,m Is delta P w,f Is an intermediate variable of (a). d, d w And (5) the ratio of the wind turbine generator set is accessed.The concentrated disturbance power estimated for the sliding mode disturbance observer. B (B) w The constant of the power response transfer function is supported for the active frequency.
Substituting equation (19) into equation (14), the system frequency state equation can be converted into the following form:
wherein:b is a system parameter matrix s ＝[0 1] T To control the matrix, Δx s ＝[Δf Δη] T For a system state variable matrix redesigned according to control objectives, u=Δp f Is a control item. ΔP f An additional power control signal is output for the sliding mode frequency controller. d, d w And (5) the ratio of the wind turbine generator set is accessed. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively.
Based on equation (20), the control term u can directly act on the system state variable Δζ. The sliding mode variable can thus be designed as:
s w ＝Δζ-[K 1 K 2 ]Δx s ＝Δζ-KΔx s ； (21)
wherein: k is a sliding mode surface matrix. Δx s ＝[ΔfΔη] T For a system state variable matrix redesigned in accordance with the control target, Δζ is a system state variable. When Δζ=kΔx by adjusting the control term u s In the process, the dynamic motion of the system is constrained to the designed sliding mode surface s w On=0, the system frequency state equation shown in equation (20) can be converted into:
obviously, for the linear system shown in formula (22), matrix A can be configured by designing the sliding surface matrix K cl To obtain the desired system dynamic performance. In general, some linear system control design methods, such as eigenvalue assignment methods or optimal sliding mode fluid design, may be used.
In order to achieve the expected control effect, the linear secondary adjustment method is selected to design the sliding mode surface matrix K, and the cost function is selected as follows:
wherein:are weight matrices that together determine a system state vector Deltax s And the specific gravity of the input vector Δζ.
By the variant (23), a standard quadratic cost function can be obtained:
wherein: intermediate variable
To minimize the cost function J, the matrix K can be designed according to the Riccati equation:
/>
wherein: p is the only solution to the Riccati equation, which can be obtained by:
step 5: and designing a sliding mode control rate of the driving system on a sliding mode surface based on a super-torsion sliding mode algorithm, and constructing a sliding mode frequency controller to enable the frequency modulation power tracking of the wind turbine to concentrate disturbance power.
The key to achieving the control objective is to ensure that the system is driven onto the slip-form surface, for which purpose the slip-form control rate u=u e +u s The structure can be as follows:
wherein: k isA sliding mode surface matrix. s is(s) w Is a sliding mode variable.Is a system parameter matrix, b s ＝[0 1] T Is a control matrix, deltax s ＝[ΔfΔη] T Is a state variable. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. d, d w And (5) the ratio of the wind turbine generator set is accessed. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively. v represents the sliding mode approach rate based on the super-warping algorithm, and can be expressed as:
wherein: s is(s) w Is a sliding mode variable. Gamma ray 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller. sign is a sign function.
In combination with (21) and (27), the system frequency state equation (20) may be rewritten to include only the system state vector Δx s And sliding mode variable s w The form of (2):
wherein:b is a system parameter matrix s ＝[0 1] T To control the matrix, Δx s ＝[ΔfΔη] T D for the system state variable matrix redesigned according to the control objective w And (5) the ratio of the wind turbine generator set is accessed. K is a sliding mode surface matrix. v denotes the sliding mode approach rate based on the super-warping algorithm. H s 、D s The inertia constant and the damping coefficient of the power system are respectively. A is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively. Disturbance item- >Representing unmodeled errors, parameter uncertainties and system disturbances, +.>The rewriteable is:
wherein: s is(s) w Is a sliding mode variable. Gamma ray 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller. sign is a sign function.Representing the differential of the disturbance term. Due to the small unmodeled errors, parameter uncertainties, and system disturbances, reasonable assumptions 2 can be made: there is a positive constant D 2 Satisfy->
Step 6: and a Lyapunov method is adopted to construct a Lyapunov function to determine the parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller, so that the proposed control method can be operated globally and stably.
The premise of achieving the control target is that the entire system can converge to a steady state. The parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller can be represented by the following inequality constraint:
wherein: d (D) 1 、D 2 The boundaries of the concentrated disturbance power differential and the system frequency disturbance term, respectively. ψ= [ - ρ 1 2] T ，λ min {U w Is a semi-positive definite matrix U w Is used to determine the minimum characteristic value of the (c),λ min {N w is a semi-positive definite matrix N w Is the minimum characteristic value of U w 、N w Can be expressed as:
wherein: h s Is an inertia constant of the power system. ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively. Gamma ray 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller.
For the above-mentioned range of values, it is verified as follows:
(1) Sliding mode disturbance observer
Theorem 1: based on hypothesis 1, if ρ 1 And ρ 2 Satisfy the formulas (31) and (33), e f And e d Will converge to the origin in a limited time.
And (3) proving: and (3) sliding mode dynamic of the sliding mode disturbance observer shown in the formula (18). The Lyapunov function V can be used 1 The selection is as follows:
wherein:alpha is a symmetric positive definite matrix. ρ 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively. Thus, the following inequality holds:
wherein: lambda alpha represents the eigenvalue of matrix alpha and subscripts "max" and "min" represent the maximum and minimum eigenvalues of matrix alpha, respectively.
Lyapunov function V along vector ζ 1 The derivative of (2) can be obtained as:
/>
wherein:ψ＝[-ρ 1 2] T 。
due to U w Is also a symmetrical positive definite matrix, and can obtain lambda { U } w }>Conclusion of 0. Thus, based on assumption 1 and formulas (36), (37), the following inequality holds:
wherein ε is represented as:
in order to satisfy the combination of (38), (39)Epsilon needs to be positive, i.e. satisfy equations (31) and (33). Thus, according to the comparison principle, all system trajectories of the sliding variable dynamics shown in equation (18) can converge to the origin within a limited time. This means that the sliding mode disturbance observer is convergent and stable.
(2) Sliding mode frequency controller
Theorem 2: under the parameter conditions in equations (32), (34), all the motion trajectories of system equation (29) will converge to the slip-form surface s in a finite time for any initial condition w On=0.
And (3) proving: and (3) sliding mode dynamic of the sliding mode frequency controller shown in the formula (29). Can be used forLyapunov function V 2 The selection is as follows:
in the formula, xi= [ xi ] 1 ξ 2 ] T ＝[|s w | 1/2 sign(s w )z] T Beta is a symmetric positive definite matrix.
Obviously, the selected Lyapunov function V 2 And V 1 Is similar, so the proving process is also the same, and can be directly obtained:
wherein δ is represented as:
similarly, when gamma 1 And gamma 2 When the value range of (2) satisfies the formulas (32), (34), δ can be obtained<0,This means that the system shown in equation (29) will converge to the slip-form surface in a finite time under any initial condition.
TABLE 1 synchronous machine set parameters
TABLE 2 wind turbine parameters
To verify the present inventionThe effectiveness and superiority of the control method are evident, firstly, a system frequency response model which is shown in figure 2 and contains wind turbine generator sets and participates in frequency modulation is built, parameters shown in tables 1 and 2 are adopted for synchronous unit parameters and wind turbine generator set parameters, and the power system is low in inertia. And obtaining parameters of the sliding mode surface matrix K by adopting a linear secondary adjustment method. The damping of the system is shown in fig. 5 under various parameters of the slip-form surface matrix K. For a linear system represented by equation (29), a system state variable Δx is desired s With slow and small variations, i.e. the frequency deviation deltaf and the tracking error deltaeta of the wind turbines are very small. Thus in this test, the parameter of K is designed to be [ -60.14, -63.55]The damping ratio was 8.93 and the system was tuned to an overdamped system. Based on the stability constraint ranges of equations (31), (32), and the desired convergence speed, the sliding mode disturbance observer and sliding mode frequency controller parameters are set to: ρ 1 ＝1248，ρ 2 ＝122，γ 1 ＝2420，γ 2 =62.89. Finally, the following 2 simulation examples are set for simulation:
calculation example 1: under uncertain load disturbance, comparing the sliding mode disturbance observer with a generalized extended state observer, and comparing the sliding mode frequency controller with an optimized frequency control based on a PID controller.
Under the uncertain load disturbance shown in fig. 6 (a), the observation result of the concentrated disturbance power is shown in fig. 7, it can be seen that both the sliding mode disturbance observer and the generalized extended state observer can realize the estimation of the concentrated disturbance power of the system, and the estimation result of the sliding mode disturbance observer is closer to the actual value. Meanwhile, fig. 7 (b) and (c) show that the total estimated error (+|Δp) of the proposed sliding mode disturbance observer d,error I dt) is smaller and the estimation speed is faster. Thus, the proposed sliding mode disturbance observer can estimate the actual system-focused disturbance power more accurately, and the estimated result can be applied to the sliding mode frequency controller.
Fig. 8 is an active frequency support result under an uncertainty load disturbance. It can be seen from fig. 8 (a) that the maximum frequency deviation of the proposed strategy is smaller than the optimized frequency control strategy each time a load fluctuation occurs, and that the system frequency deviation can be eliminated faster and smoother. Taking the load fluctuation occurring at 380s as an example, it can be found that the maximum frequency deviation under the proposed strategy and the optimized frequency control strategy is 0.0121Hz and 0.0139Hz, respectively, the deviation is reduced by 12.95%. Under the proposed strategy, the frequency deviation is smoothly eliminated within 21.8s, while optimizing the frequency control strategy requires more than 80s, a speed boost of 73.51%. As shown in fig. 8 (b), the total system frequency deviation (+|Δf|dt) increases gradually over time, the total system frequency deviation of the proposed strategy is 0.1749, the optimal frequency control is 0.2552, and the reduction is 31.47%. As can be seen from fig. 8 (c), under the optimized frequency control, the frequency adjustment power of the fan output will decrease with the decrease of the frequency deviation due to the limitation of the PID controller, and it is difficult to achieve the ideal frequency adjustment effect, which is also the reason that the frequency deviation elimination time is long. The proposed strategy is based on a designed sliding mode surface, and the frequency adjustment power output by the fan is utilized to quickly track the estimated concentrated disturbance power, so that the influence of frequency deviation reduction is avoided, and the expected frequency adjustment performance is realized. And because the concentrated disturbance power comprises the synchronous machine frequency response power, the wind turbine generator frequency support power is reduced along with the increase of the synchronous machine frequency response power in the process of tracking the concentrated disturbance power, and the coordination of the synchronous machine and the wind turbine generator frequency modulation task is realized. As can be seen from fig. 8 (d), the dc side capacitance is constant at 0, which will not affect the proposed frequency active support control strategy, and embody the compatibility of the proposed power active smoothing strategy. Thus, under load fluctuations, the proposed strategy improves frequency dynamics compared to the optimized frequency control strategy.
Calculation example 2: under uncertain wind speed disturbance, comparing the sliding mode disturbance observer with a generalized extended state observer, and comparing the sliding mode frequency controller with an optimized frequency control based on a PID controller.
As shown in fig. 9 (a) and (b), the sliding mode disturbance observer proposed under the uncertain wind speed disturbance shown in fig. 6 (b) can track the actual concentrated disturbance power faster and more accurately. As can be seen from fig. 9 (c), the total error of the proposed sliding mode disturbance observer is 0.0003, almost negligible, and significantly smaller than the total estimated error 0.0703 of the generalized extended state observer. Overall, the overall estimation error at wind speed disturbances is significantly reduced compared to load disturbances. The sliding mode disturbance observer is constructed by the method, the linear model of the output power of the wind turbine is included, the output power of the wind turbine is accurately reflected, and the sliding mode algorithm has strong anti-interference capability.
As can be seen from the active frequency support results under uncertainty wind speed perturbation fig. 10 (a) and (b), the frequency fluctuation range under the proposed strategy is significantly reduced compared to the optimized frequency control strategy, and the total system frequency deviation is smaller, reduced by 26.53%. As shown in fig. 10 (c), in the optimized frequency control strategy, the PID controller reduces the smoothing effect on the power when the frequency deviation is reduced, and increases the fan output power deviation when the frequency deviation fluctuates around 0, due to the shortage of the PID controller. For the proposed strategy, the fan output power deviation is smoother, with less impact on system frequency. As can be seen from fig. 10 (d), under the active power smoothing strategy, the direct-current side capacitance increases with the increase of the fan output power deviation, absorbs power, smoothes the fan output power deviation, and vice versa, provides smoother wind power for the active frequency support control strategy, suppresses the system frequency fluctuation in advance, and reduces the frequency modulation burden. Therefore, the proposed strategy can quickly smooth the fan output power deviation according to the frequency deviation and the concentrated disturbance power, thereby effectively coping with the influence of the uncertain wind speed disturbance on the system frequency.
The above examples merely illustrate specific embodiments of the application, which are described in more detail and are not to be construed as limiting the scope of the application. It should be noted that it is possible for a person skilled in the art to make several variants and modifications without departing from the technical idea of the application, which fall within the scope of protection of the application.
Claims (8)
1. A wind turbine generator active frequency support control method based on a sliding mode algorithm is characterized by comprising the following steps:
step 1: combining a traditional frequency response model and a wind turbine generator load shedding output power linearization model to construct a system frequency response model containing wind turbine generator participation in frequency modulation;
step 2: optimizing a wind turbine load shedding output power linearization model in a system frequency response model, setting synchronous turbine frequency response power, load fluctuation and wind energy fluctuation in the system frequency response model as concentrated disturbance power, and establishing a system frequency state equation under the active frequency support of the wind turbine;
step 3: a sliding mode disturbance observer for estimating the concentrated disturbance power is designed based on a super-distortion sliding mode algorithm by taking the system frequency deviation and an additional power control signal as input signals;
Step 4: taking the system frequency deviation equal to zero and the wind turbine generator set frequency modulation power equal to the concentrated disturbance power as control targets, constructing a sliding mode surface capable of converting the system frequency state equation in the step 2 into a linear equation, and adopting a linear system control design method to design a sliding mode surface matrix according to the expected system frequency performance;
step 5: based on a super-twist sliding mode algorithm and a sliding mode surface matrix, designing a sliding mode control rate of a driving system on a sliding mode surface, and constructing a sliding mode frequency controller to enable the frequency modulation power tracking of the wind turbine to concentrate disturbance power;
step 6: and a Lyapunov method is adopted to construct a Lyapunov function to determine the parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller, so that the proposed control method can be operated globally and stably.
2. The method for controlling the active frequency support of the wind turbine generator based on the sliding mode algorithm according to claim 1, wherein the step 1 specifically comprises the following steps:
step 1.1: the method comprises the steps of obtaining a traditional frequency response model, wherein the traditional frequency response model is used for reflecting system frequency change under unbalanced power and comprises synchronous unit response and system inertia response, and the traditional frequency response model is respectively expressed as:
Wherein: Δf, ΔP u Respectively the system frequency deviation and the system unbalanced power, N is the number of synchronous units and F Hi The proportion of the output power of the high-pressure boiler of the turbine part of the ith synchronous unit, K mi Mechanical power gain factor R for ith synchronous machine set i Is the difference adjustment coefficient T of the ith synchronous machine set gi The time constant of the speed regulator part of the ith synchronous unit is k, the automatic power generation control parameter is d s To synchronize the access proportion of the machine set, H s 、D s Respectively a system inertia constant and a system damping;
step 1.2: obtaining a wind turbine generator load shedding output power linearization model, wherein the wind turbine generator load shedding output power linearization model comprises a wind energy capturing part, a rotor speed response part and an active power response part, which are respectively expressed as:
wherein: ΔP m 、Δω r 、ΔP e 、ΔP del 、ΔP f Respectively the mechanical power variable quantity, the rotor speed variable quantity, the active power variable quantity and the load-shedding active power variable quantity of the wind turbine generatorThe rate change, the additional power control signal,representation and Δω r Related wind energy capture transfer function, +.>Representation and DeltaV w Related wind energy capture transfer function, +.>Representing a rotor speed response transfer function related to the unbalanced power ΔP>Representation and Δω r An associated load shedding active power response transfer function; expressed as:
step 1.3: acquiring a system frequency response model based on step 1.1 and step 1.2 can be expressed as:
wherein: h s 、D s Respectively a system inertia constant, a system damping, delta P s For the response part of the synchronous machine set in the traditional frequency response model, delta P e Active power response part delta P in output power linearization model for load shedding of wind turbine generator w Active power variable quantity, delta P, is output for wind turbine generator L For load fluctuation, d s 、d w G is the access proportion of the synchronous unit and the wind turbine unit respectively s (s) is the traditional function of the response of the synchronous machine set, and Δf is the frequency deviation.
3. The method for controlling the active frequency support of the wind turbine generator set based on the sliding mode algorithm according to claim 2, wherein the step 2 specifically comprises the following steps:
step 2.1: the comprehensive formulas (3) to (9) are used for obtaining the active frequency support transfer function of the wind turbine, and the wind energy fluctuation transfer function of the wind turbine is respectively expressed as follows:
wherein: h w 、D w Respectively the inertia constant and damping coefficient omega of the wind turbine generator rdel0 For the rotor speed of the wind turbine at a stable operating point,representation and Δω r Related wind energy capture transfer function, +. >Representation and DeltaV w Related wind energy capture transfer function, +.>Representing the rotor speed response transfer function in relation to the unbalance power ap,representation and Δω r Related load shedding active power response transfer function, A w 、B w Supporting a constant of a transfer function for the active frequency of the wind turbine generator; c (C) w The constant of the wind energy fluctuation transfer function of the wind turbine generator;
step 2.2: decomposing and deforming the active frequency support transfer function of the wind turbine in the system frequency response model, wherein the active frequency support transfer function of the wind turbine can be divided into a control signal delta P with additional power f The related active frequency supports the power intermediate variable response transfer function, and the intermediate variable deltap w,m The associated active frequency-dependent power response transfer functions are expressed as:
wherein: h w 、D w Respectively the inertia constant and damping coefficient omega of the wind turbine generator rdel0 For the rotor speed of the wind turbine at a stable operating point,for variation of rotor speed delta omega r Related mechanical power response transfer function, +.>For the change quantity delta omega of the speed of the rotor under the load-shedding operation of the wind turbine generator r Related onesA power response transfer function, A w 、B w The constant of the response transfer function of the intermediate variable of the active frequency support power and the constant of the response transfer function of the active frequency support power are respectively;
Step 2.3: based on a system frequency response model and in comprehensive formulas (1), (2), (11), (12) and (13), a system frequency state equation under the support of the active frequency of the wind turbine is expressed as follows:
wherein:as a system parameter matrix, Δx= [ ΔfΔp ] w,f ΔP w,m ] T As a system state variable matrix, u=Δp f As control term, ΔP f An additional power control signal output for the sliding mode frequency controller; h s 、D s Respectively an inertia constant and a damping coefficient of the power system, wherein Deltaf is a system frequency deviation and DeltaP w,f For active frequency support power provided by wind turbines ΔP w,m Is delta P w,f Intermediate variable, ΔP of (1) d ＝ΔP L -ΔP s -ΔP w,v To concentrate the disturbance power ΔP L For load fluctuation, ΔP s For synchronizing the frequency supporting dynamics of the unit, delta P w,v D is wind energy fluctuation caused by wind speed fluctuation w 、d s The access proportion of the wind turbine generator and the access proportion of the synchronous machine set are respectively; a is that w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively.
4. The method for controlling the active frequency support of the wind turbine generator set based on the sliding mode algorithm according to claim 3, wherein the step 3 is specifically as follows:
using an external system frequency offset Δf and an internal slip-mode frequency controller output Additional power control signal ΔP f Accurate estimation of the concentrated disturbance power is realized, and the method is expressed as follows:
；
wherein: h s 、D s Respectively the inertia constant and the damping coefficient of the power system, d w The proportion of the wind turbine generator is accessed,systematic frequency deviation estimated for sliding mode disturbance observer, +.>Concentrated disturbance power, ΔP, estimated for a sliding mode disturbance observer f Additional power control signal for output of sliding mode frequency controller,/->Support transfer function g for active frequency of wind turbine generator 1 、g 2 The sliding mode control items designed by the super-distortion sliding mode algorithm ensure the accuracy of the estimation result, and are expressed as follows:
wherein: h s 、D s Respectively the inertia constant and the damping coefficient, ρ, of the power system 1 、ρ 2 The normal number gains of the sliding mode disturbance observer are respectively,expressed as systematic frequency offset estimation error, sign is a sign function.
5. The method for controlling the active frequency support of the wind turbine generator based on the sliding mode algorithm according to claim 4, wherein the step 4 is specifically as follows:
step 4.1: the new state variables are defined based on the control targets of the sliding mode frequency controller, and the new state variables are defined as follows:
wherein: Δf is the system frequency deviation, ΔP w,f For active frequency support power provided by wind turbines ΔP w,m Is delta P w,f Intermediate variable d of (2) w The proportion of the wind turbine generator is accessed,concentrated disturbance power estimated for sliding mode disturbance observer, B w Supporting a constant of a power response transfer function for the active frequency;
step 4.2: substituting equation (19) into equation (14), the system frequency state equation can be converted into the following form:
wherein:b is a system parameter matrix s ＝[0 1] T To control the matrix, Δx s ＝[Δf Δη] T For a system state variable matrix redesigned according to control objectives, u=Δp f As control term, ΔP f Additional power control signal d for output by sliding mode frequency controller w For the access proportion of the wind turbine generator, H s 、D s Respectively the inertia constant and the damping coefficient of the power system, A w 、B w The constant of the response transfer function of the intermediate variable of the active frequency support power and the constant of the response transfer function of the active frequency support power are respectively;
step 4.3: based on equation (20), the sliding mode variable is designed:
s w ＝Δζ-[K 1 K 2 ]Δx s ＝Δζ-KΔx s ； (21)
wherein: k is a sliding mode surface matrix, deltax s ＝[Δf Δη] T For a system state variable matrix redesigned according to the control objective, Δζ is a system state variable;
step 4.4: since Δζ=kΔx is made by adjusting the control term u s In the process, the dynamic motion of the system is constrained to the designed sliding mode surface s w On=0, the system frequency state equation shown in equation (20) can be converted into:
Step 4.5: and selecting a linear secondary adjustment method to design a sliding mode surface matrix K.
6. The method for controlling the active frequency support of the wind turbine generator based on the sliding mode algorithm according to claim 5, wherein the step 4.5 is specifically as follows:
step 4.51: the cost function is selected, and the specific formula is as follows:
wherein:are weight matrices that together determine a system state vector Deltax s And the specific gravity of the input vector Δζ;
4.52: by the variant (23), a standard quadratic cost function can be obtained:
wherein: intermediate variable
4.53: to minimize the cost function J, the matrix K can be designed according to the Riccati equation:
wherein: p is the only solution of the Riccati equation.
7. The method for supporting and controlling the active frequency of a wind turbine generator set based on a sliding mode algorithm according to claim 6, wherein the sliding mode frequency controller in step 5 outputs an additional power control signal Δp f Controlling the wind turbine to output mechanical power reserve reserved in advance, actively supporting system frequency, and outputting an additional power control signal delta P f By slip-form control ratio u=u e +u s ＝ΔP f The decision may be expressed as:
wherein: k is a sliding mode surface matrix, s w As a variable of the sliding mode, the sliding mode is changed, Is a system parameter matrix, b s ＝[0 1] T Is a control matrix, deltax s ＝[ΔfΔη] T Is a state variable, H s 、D s Respectively the inertia constant and the damping coefficient of the power system, d w For the access proportion of the wind turbine generator, A w 、B w The constants of the active frequency support power intermediate variable response transfer function and the active frequency support power response transfer function are respectively shown as v, wherein v represents the sliding mode approach rate based on the super-distortion algorithm, and can be shown as followsThe method is shown as follows:
wherein: s is(s) w Is a sliding mode variable, gamma 1 And gamma 2 For normal number gain of the sliding mode frequency controller, sign is a sign function.
8. The method for controlling active frequency support of a wind turbine generator set based on a sliding mode algorithm according to claim 7, wherein the parameter value ranges of the sliding mode disturbance observer and the sliding mode frequency controller in the step 6 can be represented by the following inequality constraint:
wherein: d (D) 1 、D 2 Boundary of concentrated disturbance power differential and system frequency disturbance term respectively, ψ= [ - ρ 1 2] T ，λ min {U w Is a semi-positive definite matrix U w Is used to determine the minimum characteristic value of the (c),λ min {N w is a semi-positive definite matrix N w Is the minimum characteristic value of U w 、N w Can be expressed as:
wherein: ρ 1 、ρ 2 Normal number gain, gamma, of the sliding mode disturbance observer respectively 1 And gamma 2 Is the normal number gain of the sliding mode frequency controller.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310675564.4A CN117039922A (en) | 2023-06-08 | 2023-06-08 | Wind turbine generator active frequency support control method based on sliding mode algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310675564.4A CN117039922A (en) | 2023-06-08 | 2023-06-08 | Wind turbine generator active frequency support control method based on sliding mode algorithm |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117039922A true CN117039922A (en) | 2023-11-10 |
Family
ID=88632454
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310675564.4A Pending CN117039922A (en) | 2023-06-08 | 2023-06-08 | Wind turbine generator active frequency support control method based on sliding mode algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117039922A (en) |
-
2023
- 2023-06-08 CN CN202310675564.4A patent/CN117039922A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Leithead et al. | Control of variable speed wind turbines: Design task | |
| CN110397548B (en) | Multi-model predictive control method for double-fed variable-speed pumped storage unit | |
| CN110829487B (en) | Dynamic frequency prediction method for power system | |
| CN107769265B (en) | Control method and system of voltage type inverter | |
| JP2014043862A (en) | Method for controlling specified power reserve of power generator in single cycle or combined cycle gas turbine power plant, and power generating system for use with same method | |
| Yazdi et al. | Analytical modeling and inertia estimation of VSG-controlled Type 4 WTGs: Power system frequency response investigation | |
| CN108493984A (en) | Virtual synchronous generator control method suitable for photovoltaic parallel in system | |
| CN107482649A (en) | A kind of two domain interacted system LOAD FREQUENCY control methods based on frequency dividing control | |
| WO2023077740A1 (en) | Direct-current capacitor synchronous control system for grid-connected converter, and control method | |
| CN108054766A (en) | A kind of setting method, system and the device of Automatic Generation Control frequency bias coefficient | |
| CN111384730B (en) | Method for determining control parameters of virtual inertia of fan | |
| CN115441470A (en) | Adaptive virtual synchronization control method, device, medium and equipment for microgrid | |
| Hu et al. | An active primary frequency regulation strategy for grid integrated wind farms based on model predictive control | |
| CN117039922A (en) | Wind turbine generator active frequency support control method based on sliding mode algorithm | |
| CN110460113B (en) | Mechanical inertia simulation method of inverter power supply | |
| CN108539762B (en) | Frequency control system and method of wind driven generator system based on active disturbance rejection | |
| CN114069653A (en) | Wind turbine generator set improved frequency modulation control method and system considering energy storage output mode | |
| Khezami et al. | Multimodel LQ controller design for variable-speed and variable pitch wind turbines at high wind speeds | |
| Xie et al. | Virtual inertia adaptive control strategy for DFIG wind turbines based on the improved Bang-Bang control | |
| Schlipf | Prospects of multivariable feedforward control of wind turbines using lidar | |
| Tohidi et al. | Experimental study of a disturbance rejection controller for dfig based wind energy conversion systems | |
| CN107515532B (en) | System self-adaptive control method considering action threshold | |
| Hu et al. | Frequency characteristic analysis of power system considering deep peak load regulation and renewable energy injection | |
| Xiaodong et al. | Multi-objective optimization torque control of wind turbine based on LQG optimal control | |
| CN114123249B (en) | Wind power interconnection-containing power system load frequency control method based on active response of battery energy storage |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |